赤足足迹识别研究综述

doi:10.3778/j.issn.1673-9418.2307048

摘要/Abstract

摘要： 赤足足迹识别技术是图像识别技术的一个分支，在刑侦、医疗以及安全领域发挥着重要作用，有望成为一种新的进行人身识别的手段。但是该技术尚未形成较为统一的框架，也没有一个规范化的流程。为了给今后的研究人员提供指导，需要规范不同足迹图像的识别流程，并对赤足足迹识别技术相关研究进行归纳与总结。首先对赤足足迹识别研究的背景和意义进行阐述，然后回顾该技术的发展脉络，并根据采集方式的不同将赤足足迹图像分为油墨捺印足迹图像、足底扫描图像、光学足迹采集设备采集的足迹图像以及足迹压力采集系统采集的足压图像四类，并指出后两种图像是目前赤足足迹识别研究的热点。之后分别从赤足足迹数据集、图像预处理、识别方法三个方面分析赤足足迹识别技术的研究现状。其中，识别方法分为传统方法和基于深度学习的方法，后者又进一步划分为网络结构创新方法和损失函数优化方法。在给出识别方法的评价指标后，从多个方面对各种方法进行对比。最后指出该技术目前面临的问题，并对其今后的发展方向进行展望。

关键词: 图像识别, 赤足足迹, 人身识别, 足迹图像, 足压图像, 深度学习

Abstract: Bare footprint recognition technology is a branch of image recognition technology, which plays an important role in criminal investigation, medical treatment and security fields, and is expected to become a new means of personal identification. However, this technology has not yet formed a relatively unified framework, nor has it established a standardized procedure. In order to provide guidance for future researchers, it is necessary to standardize the recognition process of different bare footprint images and summarize the relevant research of bare footprint recognition technology. Firstly, the background and significance of bare footprint recognition research are expounded. Then, the development history of this technology is reviewed, and the bare footprint images are divided into four categories according to different acquisition methods: ink stamped bare footprint images, plantar scanning images, footprint images acquired by optical footprint acquisition equipment and foot pressure images acquired by footprint pressure acquisition system. It is pointed out that the latter two images are the hot spots of bare footprint recognition research at present. Then, the research status of bare footprint recognition technology is analyzed from three aspects: dataset, image preprocessing and recognition methods. Among them, the recognition methods are divided into traditional methods and deep learning-based methods, and the latter is further divided into network structure innovation methods and loss function optimization methods. The evaluation indices of identification methods are given, and various methods are compared from many aspects. Finally, the problems faced by this technology are pointed out, and its future development direction is prospected.

Key words: image recognition, bare footprint, personal identification, footprint images, foot pressure images, deep learning

王昆, 郭威, 王尊严, 韩文强. 赤足足迹识别研究综述[J]. 计算机科学与探索, 2024, 18(1): 44-57.

WANG Kun, GUO Wei, WANG Zunyan, HAN Wenqiang. Review of Bare Footprint Recognition[J]. Journal of Frontiers of Computer Science and Technology, 2024, 18(1): 44-57.

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